ST-Urban Wildlife Ecology Mgmt

Urbanization constitutes one of the greatest challenges of this century. Urban ecology is emerging as a critical transdisciplinary field, integrating the life sciences, geosciences, and social sciences to understand and manage effects of urbanization on ecosystems. In addition, urban areas provide unique opportunities for studying rapid evolutionary and behavioral changes induced by novel ecosystems and the role of humans in altering species interactions.

Landscape Ecology

Introduction to the evolving discipline of landscape ecology, with emphasis on the theoretical underpinnings Focus on ecological scaling; landscape structure; agents of landscape structure; consequences of landscape structure to populations, communities, and ecosystem processes; landscape dynamics; and landscape management. Emphasis on modeling.

PAINTING II

Painting from models, still-life, and landscape using varied techniques and conceptual frameworks. A required fee of $25 to cover group supplied materials will be charged at the time of registration. Prerequisites: 266 and permission of the instructor. Enrollment limited to 15.

DANCE AND CULTURE

Through a survey of world dance traditions from both artistic and anthropological perspectives, this course introduces students to dance as a universal human behavior, and to the many dimensions of its cultural practice -- social, religious, political, and aesthetic. Course materials are designed to provide students with a foundation for the interdisciplinary study of dance in society, and the tools necessary for analyzing cross-cultural issues in dance; they include readings, video and film viewing, research projects and dancing. L.

SEM: TOPICS IN CELL BIOLOGY

Topics course. An investigation of the emerging fields of synthetic biology and bionanotechnology drawn from semi-popular and primary research literature. In this seminar, we will focus on the central question of what can be achieved by approaching biology from an engineering mindset. Specifically, what can be learned by treating biological components (proteins and nucleic acids) and systems (signaling and metabolic networks) as interchangeable machine-like parts?
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